Smaller Than Expected

In two pre-registered studies, we investigated whether processes of imitative action regulation are facilitated after experiencing an episode of social exclusion. We reasoned that imitative action regulation effects should be more pronounced for participants who were socially excluded, providing them with an “automatic means” to socially reconnect with others. Participants played a virtual ball-tossing game to experimentally induce social exclusion or inclusion experiences. Subsequently, pairs of two participants engaged in an observational stimulus–response (SR) binding paradigm modeled after Giesen et al. (2014) : Participants observed color categorization responses in their interaction partner (trial n-1) and then executed (in)compatible responses in the subsequent trial (trial n), with observation and responding occurring in alternation. Stimulus relation (repetition vs. change) from trial n-1 to trial n was orthogonally manipulated. In both studies, stimulus-based retrieval effects of observationally acquired SR bindings were descriptively larger in socially excluded (compared with socially included) participants. However, none of the effects were statistically significant. Even a joint analysis of both experiments did not show the expected modulation. We discuss the implications of our findings for research on social exclusion effects on imitative action regulation processes.

Neural Hierarchy of Color Categorization: From Prototype Encoding to Boundary Encoding

A long-standing debate exists on how our brain assigns the fine-grained perceptual representation of color into discrete color categories. Recent functional magnetic resonance imaging (fMRI) studies have identified several regions as the candidate loci of color categorization, including the visual cortex, language-related areas, and non-language-related frontal regions, but the evidence is mixed. Distinct from most studies that emphasized the representational differences between color categories, the current study focused on the variability among members within a category (e.g., category prototypes and boundaries) to reveal category encoding in the brain. We compared and modeled brain activities evoked by color stimuli with varying distances from the category boundary in an active categorization task. The frontal areas, including the inferior and middle frontal gyri, medial superior frontal cortices, and insular cortices, showed larger responses for colors near the category boundary than those far from the boundary. In addition, the visual cortex encodes both within-category variability and cross-category differences. The left V1 in the calcarine showed greater responses to colors at the category center than to those far from the boundary, and the bilateral V4 showed enhanced responses for colors at the category center as well as colors around the boundary. The additional representational similarity analyses (RSA) revealed that the bilateral insulae and V4a carried information about cross-category differences, as cross-category colors exhibited larger dissimilarities in brain patterns than within-category colors. Our study suggested a hierarchically organized network in the human brain during active color categorization, with frontal (both lateral and medial) areas supporting domain-general decisional processes and the visual cortex encoding category structure and differences, likely due to top-down modulation.

Emergent Color Categorization in a Neural Network trained for Object Recognition

Color is a prime example of categorical perception, yet it is still unclear why and how color categories emerge. The key questions revolve around to what extent perceptual and linguistic processes shape categories. While prelinguistic infants and animals appear to treat color categorically, several recent attempts to model category formation have successfully utilized communicative concepts to predict color categories. Considering this apparent discrepancy, we take a different approach. Rather than modeling categories directly, we focus on the potential emergence of color categories as the result of acquiring basic visual skills. For this, we investigated whether color is represented categorically in a convolutional neural network (CNN) trained to recognize objects in natural images. We systematically trained novel output layers to the CNN for a color classification task, and found that clear borders arise between novel (non-training) colors that are largely invariant to the training colors. We confirmed these border locations by searching for the optimal border placement using an evolutionary algorithm that relies on the principle of categorical perception. Our findings also extend to stimuli with multiple, colored, words of varying color contrast, as well as colored objects with larger colored surfaces. These results provide strong evidence that color categorization can emerge with the development of object recognition.

Rainbows Revisited: Modeling Effective Colormap Design for Graphical Inference

Color mapping is a foundational technique for visualizing scalar data. Prior literature offers guidelines for effective colormap design, such as emphasizing luminance variation while limiting changes in hue. However, empirical studies of color are largely focused on perceptual tasks. This narrow focus inhibits our understanding of how generalizable these guidelines are, particularly to tasks like visual inference that require synthesis and judgement across multiple percepts. Furthermore, the emphasis on traditional ramp designs (e.g., sequential or diverging) may sideline other key metrics or design strategies. We study how a cognitive metric---color name variation---impacts people's ability to make model-based judgments. In two graphical inference experiments, participants saw a series of color-coded scalar fields sampled from different models and assessed the relationships between these models. Contrary to conventional guidelines, participants were more accurate when viewing colormaps that cross a variety of uniquely nameable colors. We modeled participants' performance using this metric and found that it provides a better fit to the experimental data than do existing design principles. Our findings indicate cognitive advantages for colorful maps like rainbow, which exhibit high color categorization, despite their traditionally undesirable perceptual properties. We also found no evidence that color categorization would lead observers to infer false data features. Our results provide empirically grounded metrics for predicting a colormap's performance and suggest alternative guidelines for designing new quantitative colormaps to support inference. The data and materials for this paper are available at: https://osf.io/tck2r/

Color naming and categorization depend on distinct functional brain networks

Naming a color can be understood as an act of categorization, i.e. identifying it as a member of category of colors that are referred to by the same name. But are naming and categorization equivalent cognitive processes, and consequently rely on same neural substrates? Here, we used task and resting-state fMRI, as well as behavioral measures to identify functional brain networks that modulated naming and categorization of colors. Color naming and categorization response times were modulated by different resting state connectivity networks spanning from the color-sensitive regions in the ventro-occipital cortex. Color naming correlated with the connectivity between the left posterior color region, the left medial temporal gyrus, and the left angular gyrus; whereas color categorization involved the connectivity between the bilateral posterior color regions, the left frontal, right temporal and bilateral parietal areas. The networks supporting naming and categorization did not overlap, suggesting that the two processes rely on different neural mechanisms.SignificanceWhen we name a color, we also identify it as a member of a color category, e.g. blue or yellow. Are neural processes underlying color categorization equivalent to those of color naming? Here, we address this question by measuring how individual differences in color categorization and naming response times relate to the strength of functional connections in the brain. Color naming speed correlated with left-hemispheric connectivity between the color-sensitive visual regions and the anterior temporal lobe. Color categorization speed was modulated by a different brain network, encompassing bilateral color-sensitive visual areas, and high-level executive and semantic regions. Thus, color categorization and naming performance involved distinct, non-overlapping brain networks, suggesting that the two processes depend on different neural mechanisms.